Tool forces depend on the particular tool, cutting geometry, stock (work piece), and other cutting conditions including whether or not coolant is used. Current methods for measuring tool forces require the use of a complex and expensive dedicated device such as a piezoelectric force sensor. Due to the complexity and expense of the force sensor, these methods of tool force measurement are most typically used in academic and laboratory studies.
In lieu of direct measurements, tool forces may be predicted for specified cutting conditions using a suitable process model and process model parameters, such as cutting energies. However, the prediction of tool forces using cutting energies does not eliminate the need for tool force measurements. The process model parameters are obtained by measuring tool forces under controlled circumstances and then performing a best fit of these process model parameters to a tool force model. This method provides the tool forces under a variety of cutting geometries, but is limited to the particular combination of tooling, stock, and other cutting conditions used to determine the process model parameters. The predictions are only useful if they may be extended to cutting conditions beyond those used to determine the cutting energy. However, this extension is prone to substantial errors.
The cutting energies may deviate from their nominal values for a variety of reasons. A common tool type involves placing an insert into a solid tool body, with the insert forming the cutting edge. While the tool used to determine the cutting energy may be nominally the same as that used in practice, minor variations in this insertion process can change the angle of the cutting edge. This changes the effectiveness of the particular tool, its cutting properties, and the resulting cutting energy. Another type of deviation results from the variation in the nominal properties of part materials from job to job. A particularly severe and important example of this occurs when the initial stock is a casting, where, due to the casting process, the as-cast material properties can be quite diverse.
Some tabular data of cutting energies is available for a wide range of tool and part material combinations. As with any laboratory measurements, there can be substantial deviations in the actual cutting energies from these tabulated values even for nominally the same tabulated tool and part material.
The variation in the cutting energies makes their application to tool force prediction problematic at best. Further difficulties arise when the cutting energies found in one laboratory are transferred to other applications. These difficulties are not usually discussed in the research literature, since such concerns are often counter to the interests of the researcher.
In addition, the cutting energies in the tables and in the research literature are determined for an ideal (sharp) tool. As the tool wears, the model parameters can change by as much as a factor of two or three, so precision in determining the initial model parameters may not be helpful as the machining process continues.
Thus, cutting energies can only be reliably applied to tool force prediction when the cutting energies are measured for the particular tool, part, and cutting process under consideration. Applications of the cutting energy values to other conditions may serve as a general guideline to expected values, but are not expected to be sufficiently accurate for applications such as tool condition monitoring and (Numerical Control) NC optimization.
However, in order to measure the cutting energies for a particular tool, part, and cutting process under consideration, tool forces must be determined. Since tool forces are traditionally determined using expensive and complex dedicated equipment to directly measure tool forces, obtaining cutting energies for tool force prediction for each individual job has not been an option. Thus, there remains a need for an inexpensive method for real-time measurement of tool forces and process model parameters.